scholarly journals Modeling COVID-19 Transmissions and Evaluation of Large Scale Social Restriction in Jakarta, Indonesia

2020 ◽  
Author(s):  
A. Hasan ◽  
Y. Nasution ◽  
H. Susanto ◽  
E.R.M. Putri ◽  
V.R. Tjahjono ◽  
...  
Keyword(s):  
Quantitative Evaluation ◽  
Large Scale ◽  
Reproduction Number ◽  
World Health ◽  
Transmission Model ◽  
Time Varying ◽  
Short Term ◽  
Social Restriction ◽  
Short Term Forecasting ◽  
Health Organization

AbstractThis paper presents mathematical modeling and quantitative evaluation of Large Scale Social Restriction (LSSR) in Jakarta between 10 April and 4 June 2020. The special capital region of Jakarta is the only province among 34 provinces in Indonesia with an average Testing Positivity Rate (TPR) below 5% recommended by the World Health Organization (WHO). The transmission model is based on a discrete-time compartmental epidemiological model incorporating suspected cases. The quantitative evaluation is measured based on the estimation of the time-varying effective reproduction number (ℛt). Our results show the LSSR has been successfully suppressed the spread of COVID-19 in Jakarta, which was indicated by ℛt < 1. However, once the LSSR was relaxed, the effective reproduction number increased significantly. The model is further used for short-term forecasting to mitigate the course of the pandemic.

scholarly journals COVID-19 outbreak and control in Kenya- Insights from a mathematical model

2021 ◽  
Author(s):  
Rachel Waema Mbogo ◽  
Titus Okello Orwa
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Capital City ◽  
World Health ◽  
Transmission Model ◽  
Global Public Health ◽  
The World ◽  
Rate Of Recovery ◽  
Health Organization ◽  
And Control

Abstract The coronavirus disease 2019 (COVID-19) pandemic reached Kenya in March 2020 with the initial cases reported in the capital city Nairobi and in the coastal area Mombasa. As reported by the World Health Organization, the outbreak of COVID-19 has spread across the world, killed many, collapsed economies and changed the way people live since it was first reported in Wuhan, China, in the end of 2019. As of May 25,2020 It had led to over 100,000 confirmed cases in Africa with over 3000 deaths. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.We employed a SEIHCRD mathematical transmission model with reported Kenyan data on cases of COVID-19 to estimate how transmission varies over time. The model is concise in structure, and successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak. The next generation matrix approach was adopted to calculate the basic reproduction number (R0) from the model to assess the factors driving the infection . The results from the model analysis shows that non-pharmaceutical interventions over a relatively long period is needed to effectively get rid of the COVID-19 epidemic otherwise the rate of infection will continue to increase despite the increased rate of recovery.

scholarly journals COVID-19 outbreak and control in Kenya- Insights from a mathematical model

2020 ◽  
Author(s):  
Rachel Waema Mbogo ◽  
Titus Okello Orwa
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Capital City ◽  
World Health ◽  
Transmission Model ◽  
Global Public Health ◽  
The World ◽  
Rate Of Recovery ◽  
Health Organization ◽  
And Control

Abstract The coronavirus disease 2019 ( COVID -19) pandemic reached Kenya in March 2020 with the initial cases reported in the capital city Nairobi and in the coastal area Mombasa. As reported by the World Health Organization, the outbreak of COVID -19 has spread across the world, killed many, collapsed economies and changed the way people live since it was first reported in Wuhan, China, in the end of 2019. As of May 25,2020 It had led to over 100,000 confirmed cases in Africa with over 3000 deaths. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. We employed a SEIHCRD mathematical transmission model with reported Kenyan data on cases of COVID -19 to estimate how transmission varies over time. The model is concise in structure, and successfully captures the course of the COVID -19 outbreak, and thus sheds light on understanding the trends of the outbreak. The next generation matrix approach was adopted to calculate the basic reproduction number ( $R_0$ ) from the model to assess the factors driving the infection . The results from the model analysis shows that non-pharmaceutical interventions over a relatively long period is needed to effectively get rid of the COVID -19 epidemic otherwise the rate of infection will continue to increase despite the increased rate of recovery.

scholarly journals Estimation of R0 for COVID-19 in India through different mathematical model and their comparison

2021 ◽  
Vol 8 (2) ◽  
pp. 660
Author(s):  
Nidhi Dwivedi ◽  
Sujata Gupta ◽  
Archana Dwivedi
Keyword(s):  
Basic Reproduction Number ◽  
Large Scale ◽  
Reproduction Number ◽  
Virus Disease ◽  
Central China ◽  
World Health ◽  
Family Welfare ◽  
Mathematical Methods ◽  
Novel Coronavirus ◽  
Health Organization

Background: The cases of novel coronavirus (COVID- 2019)-infected pneumonia started since the 19th of December, 2019, in Wuhan (Central China). A large scale outbreak of the disease resulted in a pandemic. This outbreak of the COVID -19 disease has spread on a wide scale. World health organization (WHO) has identified the ongoing outbreak of corona virus disease (COVID 2019) as pandemic on 11 March 2020. Basic reproduction number (R0)- is one of the most important predictors of epidemic severity. It can help to understand the path of the epidemic and to assess the effectiveness of the various interventions to control the epidemic. The purpose of this study is to estimate R0 by using five methods based on the Indian COVID-19 dataset and compare them.  Methods: We obtained data on daily confirmed, recovered and deaths cases from official site of ministry of health and family welfare. We implemented 5 mathematical methods to calculate R0. We estimated the number of active cases till 14th of April. We also compare these methods to find out the best method to predict R0.Results: The estimated R0 for the AR, EG, ML, TD, and gamma-distributed methods were 1.0004, 2.102, 1.895, 1.872 and 1.46 respectively. The computed R0 in the TD method is closer to the actual R0 and have a good fit on data as confirmed with MSE criterion.Conclusions: Awareness of the basic reproduction number of COVID-19 is useful for controlling the spread of disease and for planning. It is therefore necessary to know the best method that has better performance.

scholarly journals Pendekatan Pemodelan Matematika Dinamis Dalam Analisis Prediksi COVID-19 Sebagai Masukan Kebijakan Pemerintah Indonesia

2021 ◽  
Vol 4 (1) ◽  
pp. 1-16
Author(s):  
Ibnu Susanto Joyosemito ◽  
Narila Mutia Nasir
Keyword(s):  
Monte Carlo ◽  
Large Scale ◽  
World Health ◽  
Contact Rate ◽  
Dynamics Modeling ◽  
Social Restriction ◽  
The Government ◽  
Health Organization ◽  
Uncertain Time ◽  
The Impact

World Health Organization has declared Coronavirus Disease 2019 (COVID-19) as pandemic on March 11, 2020. It becomes a global health issue since all countries over the world including Indonesia are fighting against the disease. In order to minimize the impact of COVID-19, the government need to implement the right policy. One of the important elements in deciding the policy is by having the estimation of the COVID-19 cases using the modeling simulation. The objective of this community service activity was to provide the analysis the COVID-19 cases in Indonesia using a dynamic modeling approach. Two basic scenarios of with and without the policy implementation was simulated simultaneously with Monte Carlo method. The model results demonstrated that it needs to implement Large Scale Social Restriction (LSSR) policy to reduce the contact rate in order to reduce the spread of transmission and to extend the period of LSSR until the peak of pandemic in Indonesia is passed. The peak of pandemic under LSSR policy scenario will be reached in the middle of July. Those result were presented twice to government party. Unfortunately, the LSSR was relaxed soon after the second presentation. A precise prediction by the model was occurred when the relaxation of LSRR was implemented, then the peak of COVID-19 pandemic was shift to the uncertain time. It is suggested that the stakeholders especially the policy maker should consider the modeling analysis as a tool for helping in the policy arrangement of COVID-19 countermeasure.   Keywords: COVID-19, Dynamics Modeling, High Leverage Policy, Social Restriction   Abstrak   Organisasi Kesehatan Dunia (WHO) telah menetapkan Coronavirus Disease 2019 (COVID-19) sebagai pandemi pada 11 Maret 2020. COVID-19 menjadi isu kesehatan secara global karena semua negara di dunia termasuk Indonesia sedang berjuang melawannya. Untuk meminimalisir dampak COVID-19, pemerintah perlu menerapkan kebijakan yang tepat. Salah satu elemen penting dalam pengambilan keputusan adalah dengan melakukan estimasi kasus COVID-19 dengan menggunakan pemodelan. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk menyediakan analisis kasus COVID-19 di Indonesia dengan menggunakan pendekatan pemodelan dinamis. Dua buah basis skenario yaitu dengan dan tanpa implementasi kebijakan disimulasikan secara bersamaan dengan metode Monte Carlo. Hasil keluaran model menunjukkan perlunya penerapan kebijakan Pembatasan Sosial Berskala Besar (PSBB) untuk mengurangi laju kontak (contact rate) dengan penderita guna mengurangi penyebaran penularan dan memperpanjang periode PSBB hingga puncak pandemi COVID-19 di Indonesia terlampaui. Puncak pandemi dalam skenario kebijakan PSBB akan terjadi pada pertengahan Juli. Hasil pemodelan tersebut sudah dua kali dipresentasikan kepada pihak pemerintah. Sayangnya, PSBB diperlonggar diimplementasikan oleh pemerintah setelah presentasi kedua. Prediksi yang tepat secara kuantitatif oleh model terjadi pada saat PSBB diperlonggar diimplementasikan oleh karenanya puncak pandemi COVID-19 bergeser ke waktu yang belum dapat dipastikan. Untuk itu disarankan agar para pemangku kepentingan terutama pembuat kebijakan dapat mempertimbangkan analisis pemodelan sebagai alat bantu dalam menyusun kebijakan untuk tindakan penanggulangan COVID-19.   Kata kunci: COVID-19, Modeling, Kebijakan Berpengaruh Tinggi, Pembatasan Sosial

scholarly journals Analysis of Intervention Effectiveness Using Early Outbreak Transmission Dynamics to Guide Future Pandemic Management and Decision-Making in Kuwait

2021 ◽  
Author(s):  
Michael G. Tyshenko ◽  
Tamer Oraby ◽  
Joseph Craig Longenecker ◽  
Harri Vainio ◽  
Janvier Gasana ◽  
...  
Keyword(s):  
Decision Making ◽  
Reproduction Number ◽  
Control Measures ◽  
World Health ◽  
Transmission Model ◽  
Mobility Data ◽  
Imported Cases ◽  
Community Transmission ◽  
Health Organization ◽  
Case Data

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a World Health Organization designated pandemic that can result in severe symptoms and death that disproportionately affects older patients or those with comorbidities. Kuwait reported its first imported cases of COVID-19 on February 24, 2020. Analysis of data from the first three months of community transmission of the COVID-19 outbreak in Kuwait can provide important guidance for decision-making when dealing with future SARS-CoV-2 epidemic wave management. The analysis of intervention scenarios can help to evaluate the possible impacts of various outbreak control measures going forward which aim to reduce the effective reproduction number during the initial outbreak wave. Herein we use a modified susceptible-exposed-asymptomatic-infectious-removed (SEAIR) transmission model to estimate the outbreak dynamics of SARS-CoV-2 transmission in Kuwait. We fit case data from the first 96 days in the model to estimate the basic reproduction number and used Google mobility data to refine community contact matrices. The SEAIR modelled scenarios allow for the analysis of various interventions to determine their effectiveness. The model can help inform future pandemic wave management, not only in Kuwait but for other countries as well.

scholarly journals Heterogeneity and effectiveness analysis of COVID-19 prevention and control in major cities in China through time-varying reproduction number estimation

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qing Cheng ◽  
Zeyi Liu ◽  
Guangquan Cheng ◽  
Jincai Huang
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Reproduction Number ◽  
Correlation Method ◽  
Control Measures ◽  
Time Varying ◽  
Short Period ◽  
Significant Difference ◽  
Prevention And Control Measures ◽  
And Control

AbstractBeginning on December 31, 2019, the large-scale novel coronavirus disease 2019 (COVID-19) emerged in China. Tracking and analysing the heterogeneity and effectiveness of cities’ prevention and control of the COVID-19 epidemic is essential to design and adjust epidemic prevention and control measures. The number of newly confirmed cases in 25 of China’s most-affected cities for the COVID-19 epidemic from January 11 to February 10 was collected. The heterogeneity and effectiveness of these 25 cities’ prevention and control measures for COVID-19 were analysed by using an estimated time-varying reproduction number method and a serial correlation method. The results showed that the effective reproduction number (R) in 25 cities showed a downward trend overall, but there was a significant difference in the R change trends among cities, indicating that there was heterogeneity in the spread and control of COVID-19 in cities. Moreover, the COVID-19 control in 21 of 25 cities was effective, and the risk of infection decreased because their R had dropped below 1 by February 10, 2020. In contrast, the cities of Wuhan, Tianmen, Ezhou and Enshi still had difficulty effectively controlling the COVID-19 epidemic in a short period of time because their R was greater than 1.

scholarly journals Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Sahamoddin Khailaie ◽  
Tanmay Mitra ◽  
Arnab Bandyopadhyay ◽  
Marta Schips ◽  
Pietro Mascheroni ◽  
...  
Keyword(s):  
Structural Changes ◽  
Reproduction Number ◽  
National Level ◽  
Transmission Dynamics ◽  
Federal State ◽  
Parameter Estimates ◽  
Time Varying ◽  
Short Term ◽  
Robert Koch Institute ◽  
Federal States

Abstract Background SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. Methods We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. Results The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2–3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. Conclusions The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.

scholarly journals Forecasting of solar irradiance and ramp events with all-sky imagers

2021 ◽  
Author(s):  
Stavros-Andreas Logothetis ◽  
Vasileios Salamalikis ◽  
Stefan Wilbert ◽  
Jan Remund ◽  
Luis Zarzalejo ◽  
...  
Keyword(s):  
Solar Irradiance ◽  
Large Scale ◽  
Forecast Error ◽  
Forecast Accuracy ◽  
Short Term ◽  
Event Prediction ◽  
High Penetration ◽  
Spanish Research ◽  
Short Term Forecasting ◽  
Solar Resource

&lt;p&gt;Cloud cameras (all sky imagers/ASIs) can be used for short-term (next 20 min) forecasts of solar irradiance. For this reason, several experimental and operational solutions emerged in the last decade with different approaches in terms of instrument types and forecast algorithms. Moreover, few commercial and semi-prototype systems are already available or being investigated. So far, the uncertainty of the predictions cannot be fully compared, as previously published tests were carried out during different periods and at different locations. In this study, the results from a benchmark exercise are presented in order to qualify the current ASI-based short-term forecasting solutions and examine their accuracy. This first comparative measurement campaign carried out as part of the IEA PVPS Task 16 (https://iea-pvps.org/research-tasks/solar-resource-for-high-penetration-and-large-scale-applications/). A 3-month observation campaign (from August to December 2019) took place at Plataforma Solar de Almeria of the Spanish research center CIEMAT including five different ASI systems and a network of high-quality measurements of solar irradiance and other atmospheric parameters. Forecasted time-series of global horizontal irradiance are compared with ground-based measurements and two persistence models to identify strengths and weaknesses of each approach and define best practices of ASI-based forecasts. The statistical analysis is divided into seven cloud classes to interpret the different cloud type effect on ASIs forecast accuracy. For every cloud cluster, at least three ASIs outperform persistence models, in terms of forecast error, highlighting their performance capabilities. The feasibility of ASIs on ramp event detection is also investigated, applying different approaches of ramp event prediction. The revealed findings are promising in terms of overall performance of ASIs as well as their forecasting capabilities in ramp detection. &amp;#160;&lt;/p&gt;

scholarly journals COVID-19 pandemic. Effects of stress

2020 ◽  
Vol 1 (2) ◽  
pp. 16-24
Author(s):  
Elena S. Akarachkova ◽  
◽  
Anton A. Beliaev ◽  
Dmitrii V. Blinov ◽  
Evgenii V. Bugorskii ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Health Care ◽  
Preventive Health Care ◽  
Preventive Health ◽  
World Health ◽  
Social Stability ◽  
Short Term ◽  
Health Organization

World Health Organization declared COVID-19 outbreak a pandemic on March 11, 2020. Fear of illness, self-isolation/quarantine, and reduced quality of life dramatically increased the prevalence of stress-related disorders in the population. Therefore, it is necessary to implement the preventive health-care measures aimed at short-term and long-term COVID-19 pandemic consequences reduction and promotion of social stability.

Development of Herbal Ayurvedic Formulation as Digestive Tablets, Evaluation of it’s Pharmaceutical, Pharmacognostic Parameters and Screening of its Antioxidant Potential

2021 ◽  
pp. 5849-5855
Author(s):  
Vikas Sharma ◽  
Chandana Majee ◽  
Rahul Kaushik ◽  
Shivani Saxena ◽  
Salahuddin Salahuddin ◽  
...  
Keyword(s):  
Large Scale ◽  
Volatile Oil ◽  
Antioxidant Potential ◽  
World Health ◽  
Wet Granulation ◽  
Scale Production ◽  
Human Beings ◽  
Weight Variation ◽  
Health Organization ◽  
Average Size

Herbal digestive tablets are meant for treating indigestion problems. The indigestion problem is one of the major problems of all (the) ages of human beings. As trends for eating fast foods is increasing, simultaneously the improper digestion also tends to increase. There are a number of digestive tablets in the market but in attempt to improve their taste the actual motto behind their use is masked. To combat the indigestion problems, in the present study an attempt has been made to formulate, develop and evaluate herbal digestive tablets. The formula of the digestive tablet has been decided after deep review of Ayurvedic formulary of India. The ingredients of this formulation have been procured from authentic sources. The wet granulation method was used to prepare the granules for punching the tablets. After preparation, the herbal digestive tablets were subjected to various pharmaceutical evaluations and quality control evaluations as per the guidelines from World Health Organization (WHO). The formulation was also subjected to antioxidant screening using Phosphomolybdenum method. The digestive tablets are obtained as light brown-colored round tablets with pleasant odour and spicy taste with an average size of 8mm and smooth edges. Maximum extractive value was observed as 34% in methanol with a total ash value of 10.16%. Other parameters reported as bitterness value- 0.69 units, volatile oil content-8%, loss on drying- 12.3%, swelling and foaming index of 0.27 and less than 100 respectively. The tablets showed a total antioxidant potential of 0.51mg/mg as Ascorbic acid equivalent. Tablets also pass various pharmaceutical evaluation parameters like hardness, friability, weight variation, and disintegration test. Herbal digestive tablets have very excellent taste due to less bitter drugs. The tablet formula can be applied to prepare large scale production of digestive tablets.

Sign in / Sign up

Export Citation Format

Share Document